Triple
T21552459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple A10 Fusion |
E531795
|
entity |
| Predicate | coreCountEfficiency |
P11225
|
FINISHED |
| Object | 2 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 2 | Statement: [Apple A10 Fusion, coreCountEfficiency, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreCountEfficiency Context triple: [Apple A10 Fusion, coreCountEfficiency, 2]
-
A.
efficiencyCores
chosen
Indicates that the related cores are optimized for energy-efficient, low-power processing rather than maximum performance.
-
B.
coreCountCPU
Indicates the number of processing cores that a CPU has.
-
C.
bigCoreCount
Indicates that an entity (such as a processor or system) has a relatively large number of cores compared to a typical or baseline configuration.
-
D.
smallCoreCount
Indicates that an entity has a relatively low number of processing cores compared to typical or expected configurations.
-
E.
performanceCores
Indicates a relationship where certain cores within a processor are designated as high-performance cores optimized for speed and intensive tasks.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0c460232c81908de2c3819d17c00e |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeb59375f481909d9e2b66d18c7c32 |
completed | April 27, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69e6320766308190ba5dca2f7c826aa4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:29 p.m.